From May 2022, I will embark on a new 3-year project funded by Queensland Government. In this project, I will work with the industry partner, Verterra, and the Department of Environmental Science (DES), to develop advanced Artificial Intelligence (AI) techniques to create the first AI-enabled innovative monitoring and decision software platform for mine site rehabilitation. The employment of advanced AI techniques will allow mine rehabilitation to be assessed many times faster, more accurately, and the rehabilitation strategy design to be theory-proven, site-tailored and progressively adaptive compared to conventional manual practices.

My responsibility is to collaborate with great colleagues from the Signal, Artificial Intelligence and Video Technology (SAIVT) program and multiple disciplines across QUT to apply computer vision, machine learning and AI to solve real-world problems. We have been working on interesting government and industry projects such as airport surveillance, adversarial attacks on vision tasks, UAV-based monitoring solution for mining rehab and digital agriculture, epilepsy patient behaviour understanding, and sport analytics. At QUT, I have also been lecturing and coordinating under-graduate and post-graduate courses related to machine learning and computer vision, including PCB593 Digital Image Processing, CAB420 Introduction to Machine Learning, IFN680 Advanced Topics in Artificial Intelligence.

The Image and Vision Computing journal has a 2020 Impact Factor of 2.818.

The IEEE Access journal is a Q1 journal in Computer Science with a 2020 Impact Factor of 3.367.

Iris Recognition in the frequency domain

Digital Image ProcessingAdvanced Image ProcessingProgramming Language

Thesis project: Uncooperative human identification at a distance using face and irisImproving recognition performance of long range human identification systems based on face and iris by super-resolution and multimodal biometric fusion.